Simulink implementation of RLS algorithm for resilient artefacts removal in ECG signal
by Vuyyuru Tejaswi; A. Surendar; N. Srikanta
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 16, No. 3/4, 2020

Abstract: Noise is the undesired signal which affects the desired signal. This noise has been a serious problem which is affecting the signals during transmission of information. In this project, two different noisy signals are considered they are speech signal and ECG signal. The speech signals are taken from the NOIZEUS database and ECG signals from Physio Net ECG database. The major noises affecting the ECG signal are baseline wander, electrode motion, power line interference, muscle artefact noises. The baseline wander noise which is caused due to patient movement, breathing and bad electrode contact to skin, electrode motion noise occurs when electrode moves away from the skin which leads to impedance changes resulting in variations in ECG, muscle artefact noise which is caused due to contraction of other muscles besides the heart. Simulink model is designed for cancelling the noise from the noisy signals. The adaptive algorithm that is chosen is the RLS algorithm because it has faster convergence rate when compared to other algorithms like LMS, NLMS and RLS. The Simulink model is tested for different cases to show that the model works efficiently and the performance can be observed from the mean square error obtained.

Online publication date: Mon, 01-Jun-2020

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